Application of cuckoo search algorithm to estimate peak particle velocity in mine blasting

Fouladgar, Nazanin; Hasanipanah, Mahdi; Amnieh, Hassan Bakhshandeh

doi:10.1007/s00366-016-0463-0

Cited by 66 publications

(21 citation statements)

References 30 publications

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“…In another study by Fouladgar et al, a series of conventional experimental relations and a new metaheuristic algorithm called the cuckoo search algorithm, were used to estimate the peak particle velocity in the mine blasting. The obtained results clearly showed the power and ability of this metaheuristic algorithm in comparison to others experimental relations for predicting the peak particle velocity (Fouladgar, Hasanipanah, & Amnieh, 2017). A study was conducted by Yari et al for ranking the blasting patterns to enhance the productivity and production.…”

Section: Introductionmentioning

confidence: 63%

Implementation of an optimized binary classification by GMDH‐type neural network algorithm for predicting the blast produced ground vibration

2020

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Ground vibration is one of the most important undesired phenomena resulting from blasting operations imposing damages to facilities and buildings on the one hand, and creating environmental problems in open pit mining on the other. Therefore, the present study aims to provide an optimized classification binary model to identify the blasting patterns with an acceptable ground vibration intensity to reduce the damages resulting from this artificial phenomenon. This study uses a binary method to provide an optimized classification model for predicting and evaluating the blasting patterns with the minimum ground vibration. Group Method of Data Handling-Type Neural Network is used as one of the most practical optimization algorithms to solve complicated and uncertain problems in this modelling. In this study, by collecting the data of 52 different blasting patterns from Soungun copper mine, some of the most important geometric properties and the amount of ammonium nitrate fuel oil consumed in each blasting pattern are recorded. In addition, based on expertise and experience of experts, the degree of ground vibration produced by each blasting is qualitatively classified into four different ranges of very high, high, normal and low in the form of unacceptable (very high and High) and acceptable (normal and low) clusters. Based on the results obtained from the analyses, the developed model has a high flexibility and ability in the binary prediction of blasting patterns with an acceptable vibration magnitude.

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Section: Introductionmentioning

confidence: 63%

Implementation of an optimized binary classification by GMDH‐type neural network algorithm for predicting the blast produced ground vibration

2020

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“…e PPV critical value of the rock mass is shown in Table 7 [35,36]. Based on the integrity of 13.7 m medium sandstone, the demarcation point corresponding to the rock PPV is obtained.…”

Section: Numerical Results and Analysismentioning

confidence: 99%

Analysis and Application on Controlling Thick Hard Roof Caving with Deep-Hole Position Presplitting Blasting

Chen

2018

Advances in Civil Engineering

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For the thick hard roof (THR) in Datong mining area, mining operations often led to large-scale hanging-roof and frequent and strong strata behavior, threatening mining safety seriously. Based on the instability mechanism, the fracture model for THR was established, including rock blocks articulation and combined cantilever beam, and the limit initial and periodic intervals of THR were determined to be 36.0 m and 8.0 m, respectively. The study proposed the deep-hole presplitting blasting (DPB) for weakening THR for mitigating strong strata behaviors. Blasting-induced fracture characteristics were calculated, determining the charging coefficient and holes spacing. LS-DYNA was employed for establishing a DPB model to analyze crack evolution under the synergistic action of blasting stress wave and detonation gas and the attenuation characteristics for rock peak particle velocity, verifying the rationality of blasting parameters. Field measurement analysis indicated that the immediate roof induced a timely collapse to fill the goaf and the THR was effectively cut off near the presplitting line. Meanwhile, the working resistance was utilized with safety allowance. The field application showed the DPB on controlled THR caving achieved the significant effect.

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“…M. Hasanipanah proposed an imperialistic competitivealgorithm-based fuzzy system to predict mine blasting [31]. Nazanin Fouladgar and Mahdi Hasanipanah used the cuckoo search algorithm to estimate the peak particle velocity in mine blasting [32]. Maryam Amiri, Hassan Bakhshandeh Amnieh, and Mahdi Hasanipanah combined artificial neural network and K-nearest neighbour models to predict the blast-induced ground vibration and air-overpressure [33].…”

Section: Discussionmentioning

confidence: 99%

Stability Analysis of Underground Multicavities in Bench Blasting Vibration

Gan

Yang

Zhang

et al. 2019

Mathematical Problems in Engineering

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Underground cavities formed by underground mining activities are a potential threat to open-pit mining activities. Longtan Village Iron Mine is located in Chengde city, Hebei province, China. The open-pit mining and underground mining of Longtan Village Iron Mine are simultaneously performed. Cavities will remain after underground mining. When mining is performed on the top of the underground cavities in the open pit, concerns arise regarding the closest distance to prevent the collapse of the cavities. (The closest distance is the safe distance between the explosive and the cavities. If the distance between the explosive and the cavities is less than the closest distance, the stability of the cavities will be affected.) The collapse will endanger the safety of the workers and equipment in the open pit. Therefore, it is necessary to estimate the stability of the underground cavities near the bench blasting. In this paper, a series of bench blast tests was performed, and the site-specific attenuation relations of the PPV (Peak particle velocity) and principal frequency of Longtan Village Iron Mine were obtained. Then, an ANASYS three-dimensional numerical model was created, and the propagation of the blast wave and the response of the multicavities were calculated by LS-DYNA. The accuracy of the simulation was verified. However, the bench blast tests do not affect the stability of the cavities. The formula to calculate the closest distance was obtained, which can be used as an approximate guide when designing the bench explosion of Longtan Village Iron Mine. Workers can mine in a safe area of the open pit, and the stability of the cavities will not be affected.

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Application of cuckoo search algorithm to estimate peak particle velocity in mine blasting

Cited by 66 publications

References 30 publications

Implementation of an optimized binary classification by GMDH‐type neural network algorithm for predicting the blast produced ground vibration

Implementation of an optimized binary classification by GMDH‐type neural network algorithm for predicting the blast produced ground vibration

Analysis and Application on Controlling Thick Hard Roof Caving with Deep-Hole Position Presplitting Blasting

Stability Analysis of Underground Multicavities in Bench Blasting Vibration

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